ground/gcs/src/libs/eigen/test/product_notemporary.cpp

   1 // This file is part of Eigen, a lightweight C++ template library
   2 // for linear algebra.
   3 //
   4 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
   5 //
   6 // This Source Code Form is subject to the terms of the Mozilla
   7 // Public License v. 2.0. If a copy of the MPL was not distributed
   8 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
   9
  10 static int nb_temporaries;
  11
  12 inline void on_temporary_creation(int size) {
  13   // here's a great place to set a breakpoint when debugging failures in this test!
  14   if(size!=0) nb_temporaries++;
  15 }
  16
  17
  18 #define EIGEN_DENSE_STORAGE_CTOR_PLUGIN { on_temporary_creation(size); }
  19
  20 #include "main.h"
  21
  22 #define VERIFY_EVALUATION_COUNT(XPR,N) {\
  23     nb_temporaries = 0; \
  24     XPR; \
  25     if(nb_temporaries!=N) std::cerr << "nb_temporaries == " << nb_temporaries << "\n"; \
  26     VERIFY( (#XPR) && nb_temporaries==N ); \
  27   }
  28
  29 template<typename MatrixType> void product_notemporary(const MatrixType& m)
  30 {
  31   /* This test checks the number of temporaries created
  32    * during the evaluation of a complex expression */
  33   typedef typename MatrixType::Index Index;
  34   typedef typename MatrixType::Scalar Scalar;
  35   typedef typename MatrixType::RealScalar RealScalar;
  36   typedef Matrix<Scalar, 1, Dynamic> RowVectorType;
  37   typedef Matrix<Scalar, Dynamic, 1> ColVectorType;
  38   typedef Matrix<Scalar, Dynamic, Dynamic, ColMajor> ColMajorMatrixType;
  39   typedef Matrix<Scalar, Dynamic, Dynamic, RowMajor> RowMajorMatrixType;
  40
  41   Index rows = m.rows();
  42   Index cols = m.cols();
  43
  44   ColMajorMatrixType m1 = MatrixType::Random(rows, cols),
  45                      m2 = MatrixType::Random(rows, cols),
  46                      m3(rows, cols);
  47   RowVectorType rv1 = RowVectorType::Random(rows), rvres(rows);
  48   ColVectorType cv1 = ColVectorType::Random(cols), cvres(cols);
  49   RowMajorMatrixType rm3(rows, cols);
  50
  51   Scalar s1 = internal::random<Scalar>(),
  52          s2 = internal::random<Scalar>(),
  53          s3 = internal::random<Scalar>();
  54
  55   Index c0 = internal::random<Index>(4,cols-8),
  56         c1 = internal::random<Index>(8,cols-c0),
  57         r0 = internal::random<Index>(4,cols-8),
  58         r1 = internal::random<Index>(8,rows-r0);
  59
  60   VERIFY_EVALUATION_COUNT( m3 = (m1 * m2.adjoint()), 1);
  61   VERIFY_EVALUATION_COUNT( m3 = (m1 * m2.adjoint()).transpose(), 1);
  62   VERIFY_EVALUATION_COUNT( m3.noalias() = m1 * m2.adjoint(), 0);
  63
  64   VERIFY_EVALUATION_COUNT( m3 = s1 * (m1 * m2.transpose()), 1);
  65   VERIFY_EVALUATION_COUNT( m3 = m3 + s1 * (m1 * m2.transpose()), 1);
  66   VERIFY_EVALUATION_COUNT( m3.noalias() = s1 * (m1 * m2.transpose()), 0);
  67
  68   VERIFY_EVALUATION_COUNT( m3 = m3 + (m1 * m2.adjoint()), 1);
  69   VERIFY_EVALUATION_COUNT( m3 = m3 + (m1 * m2.adjoint()).transpose(), 1);
  70   VERIFY_EVALUATION_COUNT( m3.noalias() = m3 + m1 * m2.transpose(), 1);   // 0 in 3.3
  71   VERIFY_EVALUATION_COUNT( m3.noalias() += m3 + m1 * m2.transpose(), 1);  // 0 in 3.3
  72   VERIFY_EVALUATION_COUNT( m3.noalias() -= m3 + m1 * m2.transpose(), 1);  // 0 in 3.3
  73
  74   VERIFY_EVALUATION_COUNT( m3.noalias() = s1 * m1 * s2 * m2.adjoint(), 0);
  75   VERIFY_EVALUATION_COUNT( m3.noalias() = s1 * m1 * s2 * (m1*s3+m2*s2).adjoint(), 1);
  76   VERIFY_EVALUATION_COUNT( m3.noalias() = (s1 * m1).adjoint() * s2 * m2, 0);
  77   VERIFY_EVALUATION_COUNT( m3.noalias() += s1 * (-m1*s3).adjoint() * (s2 * m2 * s3), 0);
  78   VERIFY_EVALUATION_COUNT( m3.noalias() -= s1 * (m1.transpose() * m2), 0);
  79
  80   VERIFY_EVALUATION_COUNT(( m3.block(r0,r0,r1,r1).noalias() += -m1.block(r0,c0,r1,c1) * (s2*m2.block(r0,c0,r1,c1)).adjoint() ), 0);
  81   VERIFY_EVALUATION_COUNT(( m3.block(r0,r0,r1,r1).noalias() -= s1 * m1.block(r0,c0,r1,c1) * m2.block(c0,r0,c1,r1) ), 0);
  82
  83   // NOTE this is because the Block expression is not handled yet by our expression analyser
  84   VERIFY_EVALUATION_COUNT(( m3.block(r0,r0,r1,r1).noalias() = s1 * m1.block(r0,c0,r1,c1) * (s1*m2).block(c0,r0,c1,r1) ), 1);
  85
  86   VERIFY_EVALUATION_COUNT( m3.noalias() -= (s1 * m1).template triangularView<Lower>() * m2, 0);
  87   VERIFY_EVALUATION_COUNT( rm3.noalias() = (s1 * m1.adjoint()).template triangularView<Upper>() * (m2+m2), 1);
  88   VERIFY_EVALUATION_COUNT( rm3.noalias() = (s1 * m1.adjoint()).template triangularView<UnitUpper>() * m2.adjoint(), 0);
  89
  90   VERIFY_EVALUATION_COUNT( m3.template triangularView<Upper>() = (m1 * m2.adjoint()), 0);
  91   VERIFY_EVALUATION_COUNT( m3.template triangularView<Upper>() -= (m1 * m2.adjoint()), 0);
  92
  93   // NOTE this is because the blas_traits require innerstride==1 to avoid a temporary, but that doesn't seem to be actually needed for the triangular products
  94   VERIFY_EVALUATION_COUNT( rm3.col(c0).noalias() = (s1 * m1.adjoint()).template triangularView<UnitUpper>() * (s2*m2.row(c0)).adjoint(), 1);
  95
  96   VERIFY_EVALUATION_COUNT( m1.template triangularView<Lower>().solveInPlace(m3), 0);
  97   VERIFY_EVALUATION_COUNT( m1.adjoint().template triangularView<Lower>().solveInPlace(m3.transpose()), 0);
  98
  99   VERIFY_EVALUATION_COUNT( m3.noalias() -= (s1 * m1).adjoint().template selfadjointView<Lower>() * (-m2*s3).adjoint(), 0);
 100   VERIFY_EVALUATION_COUNT( m3.noalias() = s2 * m2.adjoint() * (s1 * m1.adjoint()).template selfadjointView<Upper>(), 0);
 101   VERIFY_EVALUATION_COUNT( rm3.noalias() = (s1 * m1.adjoint()).template selfadjointView<Lower>() * m2.adjoint(), 0);
 102
 103   // NOTE this is because the blas_traits require innerstride==1 to avoid a temporary, but that doesn't seem to be actually needed for the triangular products
 104   VERIFY_EVALUATION_COUNT( m3.col(c0).noalias() = (s1 * m1).adjoint().template selfadjointView<Lower>() * (-m2.row(c0)*s3).adjoint(), 1);
 105   VERIFY_EVALUATION_COUNT( m3.col(c0).noalias() -= (s1 * m1).adjoint().template selfadjointView<Upper>() * (-m2.row(c0)*s3).adjoint(), 1);
 106
 107   VERIFY_EVALUATION_COUNT( m3.block(r0,c0,r1,c1).noalias() += m1.block(r0,r0,r1,r1).template selfadjointView<Upper>() * (s1*m2.block(r0,c0,r1,c1)), 0);
 108   VERIFY_EVALUATION_COUNT( m3.block(r0,c0,r1,c1).noalias() = m1.block(r0,r0,r1,r1).template selfadjointView<Upper>() * m2.block(r0,c0,r1,c1), 0);
 109
 110   VERIFY_EVALUATION_COUNT( m3.template selfadjointView<Lower>().rankUpdate(m2.adjoint()), 0);
 111
 112   // Here we will get 1 temporary for each resize operation of the lhs operator; resize(r1,c1) would lead to zero temporaries
 113   m3.resize(1,1);
 114   VERIFY_EVALUATION_COUNT( m3.noalias() = m1.block(r0,r0,r1,r1).template selfadjointView<Lower>() * m2.block(r0,c0,r1,c1), 1);
 115   m3.resize(1,1);
 116   VERIFY_EVALUATION_COUNT( m3.noalias() = m1.block(r0,r0,r1,r1).template triangularView<UnitUpper>()  * m2.block(r0,c0,r1,c1), 1);
 117
 118   // Zero temporaries for lazy products ...
 119   VERIFY_EVALUATION_COUNT( Scalar tmp = 0; tmp += Scalar(RealScalar(1)) /  (m3.transpose().lazyProduct(m3)).diagonal().sum(), 0 );
 120
 121   // ... and even no temporary for even deeply (>=2) nested products
 122   VERIFY_EVALUATION_COUNT( Scalar tmp = 0; tmp += Scalar(RealScalar(1)) /  (m3.transpose() * m3).diagonal().sum(), 0 );
 123   VERIFY_EVALUATION_COUNT( Scalar tmp = 0; tmp += Scalar(RealScalar(1)) /  (m3.transpose() * m3).diagonal().array().abs().sum(), 0 );
 124
 125   // Zero temporaries for ... CoeffBasedProductMode
 126   // - does not work with GCC because of the <..>, we'ld need variadic macros ...
 127   //VERIFY_EVALUATION_COUNT( m3.col(0).head<5>() * m3.col(0).transpose() + m3.col(0).head<5>() * m3.col(0).transpose(), 0 );
 128
 129   // Check matrix * vectors
 130   VERIFY_EVALUATION_COUNT( cvres.noalias() = m1 * cv1, 0 );
 131   VERIFY_EVALUATION_COUNT( cvres.noalias() -= m1 * cv1, 0 );
 132   VERIFY_EVALUATION_COUNT( cvres.noalias() -= m1 * m2.col(0), 0 );
 133   VERIFY_EVALUATION_COUNT( cvres.noalias() -= m1 * rv1.adjoint(), 0 );
 134   VERIFY_EVALUATION_COUNT( cvres.noalias() -= m1 * m2.row(0).transpose(), 0 );
 135 }
 136
 137 void test_product_notemporary()
 138 {
 139   int s;
 140   for(int i = 0; i < g_repeat; i++) {
 141     s = internal::random<int>(16,EIGEN_TEST_MAX_SIZE);
 142     CALL_SUBTEST_1( product_notemporary(MatrixXf(s, s)) );
 143     s = internal::random<int>(16,EIGEN_TEST_MAX_SIZE);
 144     CALL_SUBTEST_2( product_notemporary(MatrixXd(s, s)) );
 145     s = internal::random<int>(16,EIGEN_TEST_MAX_SIZE/2);
 146     CALL_SUBTEST_3( product_notemporary(MatrixXcf(s,s)) );
 147     s = internal::random<int>(16,EIGEN_TEST_MAX_SIZE/2);
 148     CALL_SUBTEST_4( product_notemporary(MatrixXcd(s,s)) );
 149   }
 150 }